Both trace agents and score production traffic. HoneyHive is the broader eval platform, with experiments, CI gating, annotation queues and prompt versioning; Raindrop is narrower and production-first, built to surface recurring failures and compare changes on live users. How you plan to pay after the free tier may decide it as much as features.[1][4]
HoneyHive is a hosted, OpenTelemetry-based platform covering the full evaluation loop (tracing, experiments, online evals, annotation queues and prompt versioning), while Raindrop is a hosted production monitor that classifies live agent traffic and groups recurring failures into issues. Both are independent. HoneyHive has a free tier and then only quote-based Enterprise pricing; Raindrop has a published self-serve Pro plan.
| Decision factor | HoneyHive | Raindrop |
|---|---|---|
| Ownership | Independent; $7.4M raised in total, last announced April 2025 | Independent; Series A led by CRV in September 2026, $50M raised in total |
| Offline evals | Yes: experiments on datasets, with CI regression gating via GitHub Actions | Partial: Workshop runs evals locally; Simulations in early access |
| Production scoring | Online evals on sampled traces with LLM, code and human evaluators | Signals on every new event; Issue Detection groups recurring failures |
| Judges | LLM evaluators with your own prompts and rubrics; server-side Python evaluators | Signals drafted from a description; no custom judge prompt or model |
| Human review | Annotation queues with automations | Labelling samples and dataset members; no reviewer queue |
| Prompt tooling | Playground, prompt versioning and deployment | None documented |
| Self-hosting | Enterprise: fully self-hosted or hybrid, documented on AWS | Beta: Enterprise VPC deployment for select partners |
| After the free tier | Enterprise only, quote-based | Pro: $299 a month plus $0.003 per event |
| Capability | HoneyHive | Raindrop | Prefactor |
|---|---|---|---|
| Observe | |||
| LLM call tracing | ✓ | ✓ | ✓ |
| Multi-step agent tracing (tool calls, nested spans) | ✓ | ✓ | ✓ |
| Cost tracking | ✓ | ✓ | ✓ |
| OpenTelemetry support | ✓ | ✓ | ✓ |
| Evaluate | |||
| Offline evals (datasets, experiments) | ✓ | Partial | ✓ |
| Online evals on production traffic | ✓ | ✓ | ✓ |
| LLM-as-a-judge scoring | ✓ | Partial | ✓ |
| Code-based evaluators | ✓ | Partial | ✓ |
| Human review and annotation | ✓ | Partial | ✓ |
| Prompt versioning and playground | ✓ | — | — |
| Act on findings | |||
| Runtime controls on live agent actions | — | — | ✓ |
| Gateway or proxy in the request path | — | — | — |
| Licence and deployment | |||
| Open source | Partial | Partial | Partial |
| Self-hosting | ✓ | Partial | Partial |
HoneyHive covers the whole loop in one hosted product. You run experiments against datasets to compare prompts, models and pipelines, gate regressions in CI through GitHub Actions, score sampled production traces with LLM, code and human evaluators, route flagged traces to domain experts in annotation queues, and version and deploy prompts. Default sampling for online evals was lowered to 10% in May 2026.
Raindrop covers the production end and covers it differently. You describe a behaviour in plain language and Raindrop drafts a classifier, a Signal, that runs on every new event and backfills a sampled 90 days. Issue Detection groups recurring failures, a Triage Agent investigates them in the web app, Slack or over MCP, and Experiments compare signal rates between cohorts of live traffic. Pre-release testing relies on Workshop, an MIT-licensed local tool where a coding agent writes evals, and Simulations, which is in early access.
The key trade-off is who defines the judge. HoneyHive lets you write evaluator prompts and rubrics with Jinja2 templating and version them. Raindrop builds classifiers with its own models; you tune them by labelling samples but cannot bring your own judge prompt or model.
Both trace multi-step runs. HoneyHive offers agent graphs, trajectories, threads and, since September 2026, a conversation view. It also traces coding agents such as Claude Code, Codex CLI and Devin, and added Salesforce Agentforce and Databricks Agent Bricks tracing in August 2026. Raindrop follows every message, tool call and decision in a run, with integrations for a long list of agent frameworks, most labelled beta.
HoneyHive is built on OpenTelemetry and reads GenAI, OpenLLMetry and OpenInference conventions. Its full tracing SDK is Python; the TypeScript package is a REST client rather than an auto-instrumenting tracer, so TypeScript teams use OTLP. Raindrop has native TypeScript, Python and Go SDKs and accepts OTLP traces over HTTP, without gRPC, metrics or logs.
Neither documents run-time checks on agent actions. HoneyHive's Policies set organisation-wide evaluation and monitoring standards, and in Microsoft's ASSERT partnership HoneyHive is the observability layer while another component enforces. Raindrop analyses events after ingestion and alerts.
As of 20 October 2026, HoneyHive's Developer tier is free with 10,000 events a month, 30-day retention and up to five users. There is no published self-serve paid plan; anything above that, including self-hosting, is quote-based Enterprise. Raindrop's Hobby plan is free for 1,000 events a month, after which ingestion stops until the next month, with one custom signal and 14-day retention. Pro is $299 a month plus $0.003 per event up to 1M events, then $0.002, with unlimited retention and a 14-day trial.
Each vendor defines an event in its own way, so do not compare the free allowances one for one. Check HoneyHive's pricing and Raindrop's plans against your own traffic.
HoneyHive is a small company: its last announced funding was $7.4M in April 2025, and third-party directories list roughly 18 to 19 staff. It ships steadily, with dataset tooling and new chart types in October 2026. Raindrop announced a Series A in September 2026 that took its total to $50M.
For self-hosting, HoneyHive is further along. Its Enterprise plan offers fully self-hosted or hybrid deployment, documented on AWS with Terraform and Helm. Raindrop's self-hosting is a beta VPC deployment for select Enterprise partners.
Both track spend. HoneyHive has cost, token and latency dashboards with alerts, session-level cost, and since July 2026 usage reports by workspace and project, with per-workspace provider keys for attributing cost. Raindrop shows spend by model, provider and project from a versioned catalogue of public model rates, and its Experiments report median cost per event, which helps when a change trades quality against cost.
We sell the layer this section describes. Read it with that in mind.
Stated plainly, since Prefactor publishes this page: Prefactor is an agent evaluation platform that scores each step of a run and acts on a failing score through runtime policies, approval holds and a kill switch for a run, an agent or a team. Neither HoneyHive nor Raindrop documents blocking, guardrails or approvals on live agent actions; both observe and score. Prefactor has no prompt playground or prompt registry and its platform is hosted, so if prompt deployment or a self-hosted control plane is the requirement, HoneyHive is the better fit. See the full comparison of 15 platforms.
Reviewed against public product and documentation pages on October 20, 2026. If a vendor has changed a feature, product name, or positioning since then, send a correction and we will update it. Numbered source links in the page body point to the ordered sources below.
Prefactor scores each step of every agent run and can hold or stop an action when a score says it should not happen. Start on the free tier: 5,000 spans a month, no credit card required.
Prefactor helps teams observe, evaluate, and improve their AI agents in production, across every framework and provider.